What is a Data Lake?
A data lake is a centralized repository designed to store, process, and secure vast amounts of structured, semi-structured, and unstructured data. It stores data in its native format, allowing for the processing of diverse data types without size limitations.
Examples of Data in a Data Lake
Data lakes can store various data types, including:
- Structured data from relational databases (rows and columns)
- Semi-structured data like CSV, logs, XML, and JSON
- Unstructured data such as emails, documents, and PDFs
- Binary data including images, audio, and video
Data Lake vs. Database
While a database stores current data required for specific applications, a data lake stores both current and historical data in its raw form for analysis purposes.
SQL and Data Lakes
SQL is widely used for analysis and transformation of large data volumes in data lakes. Despite the push towards newer technologies, SQL remains a mainstay in data lake operations.
ETL and Data Lakes
ETL (Extract, Transform, Load) processes are typically associated with Data Warehouses, while ELT (Extract, Load, Transform) is more common in Data Lakes. ETL is the most common method for transferring data from source systems to a Data Warehouse.
Source: Internet
Image Credits: Semantix
Disclaimer: This post is shared for educational purposes related to technology.